The Icon Imagemap Technique for Multivariate Geospatial Data Visualization: Approach and Software System

Zhang, Xianfeng; Pazner, Micha

doi:10.1559/152304004773112758

Cited by 25 publications

(20 citation statements)

References 5 publications

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“…(I. Creusen and Hazelhoff 2012) visualized detected traffic signs on a 3D map based on GPS position of the images. (Zhang and Pazner 2004) presented an icon-based visualization technique designed for co-visualizing multiple layers of geospatial information. A common problem in visualization is that these methods require adding a large number of markers to a map which creates usability issues and the degraded performance of the map.…”

Section: Data Mining and Visualization For Roadway Inventory Managemementioning

confidence: 99%

Detection, classification, and mapping of U.S. traffic signs using google street view images for roadway inventory management

2015

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Background: Maintaining an up-to-date record of the number, type, location, and condition of high-quantity low-cost roadway assets such as traffic signs is critical to transportation inventory management systems. While, databases such as Google Street View contain street-level images of all traffic signs and are updated regularly, their potential for creating an inventory databases has not been fully explored. The key benefit of such databases is that once traffic signs are detected, their geographic coordinates can also be derived and visualized within the same platform. Methods: By leveraging Google Street View images, this paper presents a new system for creating inventories of traffic signs. Using computer vision method, traffic signs are detected and classified into four categories of regulatory, warning, stop, and yield signs by processing images extracted from Google Street View API. Considering the discriminative classification scores from all images that see a sign, the most probable location of each traffic sign is derived and shown on the Google Maps using a dynamic heat map. A data card containing information about location and type of each detected traffic sign is also created. Finally, several data mining interfaces are introduced that allow for better management of the traffic sign inventories.

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Section: Data Mining and Visualization For Roadway Inventory Managemementioning

confidence: 99%

Detection, classification, and mapping of U.S. traffic signs using google street view images for roadway inventory management

2015

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“…These glyphs visualize multivariate data by relating different variables to different facial features to form a face icon for each data object and then draw each face icon on a map (Dorling 1994). In related work, an icon-based approach has been introduced to visualize multiple variables (layers) for each location in a raster display using a multivariate icon (Zhang and Pazner 2004). Patterns in iconbased maps may be easiest to interpret if the appearance of icons has direct meaning (e.g., smiling faces representing a good socioeconomic situation).…”

Section: Visualizing Multivariate Geographic Patternsmentioning

confidence: 99%

Multivariate Analysis and Geovisualization with an Integrated Geographic Knowledge Discovery Approach

Guo¹,

Gahegan²,

MacEachren

et al. 2005

Cartography and Geographic Information Science

122

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The discovery, interpretation, and presentation of multivariate spatial patterns are important for scientific understanding of complex geographic problems. This research integrates computational, visual, and cartographic methods together to detect and visualize multivariate spatial patterns. The integrated approach is able to: (1) perform multivariate analysis, dimensional reduction, and data reduction (summarizing a large number of input data items in a moderate number of clusters) with the Self-Organizing Map (SOM); (2) encode the SOM result with a systematically designed color scheme; (3) visualize the multivariate patterns with a modified Parallel Coordinate Plot (PCP) display and a geographic map (GeoMap); and (4) support human interactions to explore and examine patterns. The research shows that such "mixed initiative" methods (computational and visual) can mitigate each other's weakness and collaboratively discover complex patterns in large geographic datasets, in an effective and efficient way.

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“…WebGIS is in deep development stage in both theory and application [3]. The traditional raster map is very inconvenient because of large transmission quantity of data, high bandwidth required, inefficient, poor quality in displaying and distortion when amplified [4]. The development and application of vector map data provides another solution.…”

Section: Introductionmentioning

confidence: 99%

Comparative Study on Visualizing Vector Graphics in WebGIS Applications with SVG and Flash Technologies

Yang

Chen³

et al. 2015

Advances in Intelligent Systems Research

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Abstract-This paper compared the performance of SVG and Flash when applied in WebGIS from different aspects, including basic characteristics, data storage, page rendering speed, interactivity etc. Through experiments and analysis, the result shows that: SVG and Flash can be used for visualizing WebGIS vector graphics. They are similar but have different characteristics. SVG, which is based on XML, has advantages in data exchange, transmission, integration and interoperability, it can be modified conveniently with low production cost. Flash has the advantage in terms of network animation, moreover, has high data compression, fast transmission and rendering speed. Finally, recommendations were made about how to choose vector map format in WebGIS.

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The Icon Imagemap Technique for Multivariate Geospatial Data Visualization: Approach and Software System

Cited by 25 publications

References 5 publications

Detection, classification, and mapping of U.S. traffic signs using google street view images for roadway inventory management

Detection, classification, and mapping of U.S. traffic signs using google street view images for roadway inventory management

Multivariate Analysis and Geovisualization with an Integrated Geographic Knowledge Discovery Approach

Comparative Study on Visualizing Vector Graphics in WebGIS Applications with SVG and Flash Technologies

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